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Principal Machine Learning Engineer

Workiva Inc.
Full-time
On-site
Ames United States of America
Software

The Principal Machine Learning Engineer at Workiva spearheads the strategic vision for advancing Machine Learning (ML) solutions, ensuring inclusivity, and fostering innovation. This role champions AI/MLOps excellence, crafting cloud infrastructure solutions to expedite AI/ML development cycles. As a technical leader, the Principal ML Engineer guides a team in creating Workiva’s Generative AI platform, empowering product teams to pioneer transformative solutions. They offer expertise and mentorship within the Machine Learning domain, driving progress through collaboration and technical acumen.


What You’ll Do

  • Shape the strategic ML roadmap, exploring new technologies and guiding leadership on ML strategies

  • Architect scalable systems with strong observability and maintain ML infrastructure

  • Lead adoption of new ML methodologies, mentoring engineers and establishing team standards

  • Collaborate with product, data, and architecture teams to integrate ML solutions via APIs and design end-to-end products

  • Manage backlog, forecast timelines, and resolve interdependencies to ensure timely delivery

  • Host and monitor ML models, develop automated tests, and support production troubleshooting (including on-call)

  • Conduct code reviews, ensure solution quality, and communicate technical issues to diverse stakeholders


What You’ll Need
Minimum Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or equivalent experience

  • Minimum 8 years of ML engineering experience

Preferred Qualifications

  • Provides technical leadership for ML initiatives, shaping strategy and guiding teams across the full ML lifecycle and toolsets

  • Designs and oversees scalable, highly available ML/MLOps solutions, ensuring production readiness and long-term sustainability

  • Evaluates and integrates emerging technologies such as Generative AI and agentic frameworks into enterprise solutions

  • Applies deep knowledge of computer science, distributed cloud systems, and databases to influence architectural decisions and performance improvements

  • Demonstrates proficiency in Python, Go, Java (or similar), Git, Docker/Kubernetes, and cloud platforms (AWS preferred)

  • Champions Agile/Scrum practices, driving alignment across multiple projects, priorities, and teams

  • Builds strong cross-functional partnerships, effectively communicating complex technical concepts to stakeholders at all levels

  • Anticipates and resolves system-level challenges, setting standards for debugging, troubleshooting, and ensuring scalable, reliable deployments


Working Conditions

  • Minimal (<10%) travel for customer research or collaboration

  • Reliable internet access for remote working opportunities

How You’ll Be Rewarded

✅ Salary range in the US: $204,000.00 - $326,000.00

✅ A discretionary bonus typically paid annually

✅ Restricted Stock Units granted at time of hire

✅ 401(k) match and comprehensive employee benefits package

The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email talentacquisition@workiva.com.

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.

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